Electrochemical study of AISI 304 stainless steel during the exposure at the disinfectant solutions with fungal suspensions

The effect of fungal suspensions on the disinfectant solution (Actisept with sodium dichloroisocyanurate as active substance, which releases 140 ppm active chlorine) and the corrosion behavior of type AISI 304 stainless steel (SS) were evaluated through linear polarization. The work presents a study of biocide Actisept solution as reference solution and the mixed solutions: reference biocide Actisept solution with three fungal suspensions (10 vol%), Aspergillus niger, Candida mycoderma, and Saccharomyces cerevisiae. The fungal suspension has an important influence on the synergistic effect of the SS corrosion in the following order: Saccharomyces cerevisiae > Candida mycoderma > Aspergillus niger. The E_corr values from the mixed solutions decreased with immersion time of the samples. In the case of Aspergillus niger, the corrosion rate was lower than that of any other type of fungal suspension tested, because the arrangement in solutions, the size and composition of Aspergillus niger spores were more favorable to protect the spores of the chemical and the electrical stressing. The results showed that there is a synergistic effect between the active substances from the disinfectant, fungal suspensions and applied potential, thus this effect can be taken into consideration for the hygienic and safety food industry.     

Comments on "Linearization method for finding Cramer-Rao bounds insignal processing" [and reply]

The authors comment that an interesting attempt was made to simplify the derivation of the Cramer-Rao bound (CRB) for the principal parameters in the so-called superimposed-signals-in-noise models. Here, we streamline the derivation in question and then go on to show how it relates to other possible derivations of the CRB. We show that the new derivation can be neatly interpreted as performing a block diagonalization of the CRB matrix, which is a sensible thing to do in the presence of nuisance parameters. Gu (see ibid., vol.48, p.543-545, Feb. 2000) replies that the interesting problem of de-coupling in Cramer-Rao bounds is algebraically and neatly approached in this article, whereas the linearization method is geometrical, with statistical interpretations     

Asymptotic bias of the high-order autoregressive estimates of sinusoidal frequencies

Fitting a high-order autoregressive model to data is often used to estimate the frequencies of sinusoids from their noisy measurements. This paper analyzes the asymptotic bias of the frequency estimates obtained by this method. It is shown that the bias decreases significantly with increasing model order.The work of B. Friedlander was supported by the Office of Naval Research under contract No. N000014-84-C-0408.     

Securing User-Controlled Routing Infrastructures

Designing infrastructures that give untrusted third parties (such as end-hosts) control over routing is a promising research direction for achieving flexible and efficient communication. However, serious concerns remain over the deployment of such infrastructures, particularly the new security vulnerabilities they introduce. The flexible control plane of these infrastructures can be exploited to launch many types of powerful attacks with little effort. In this paper, we make several contributions towards studying security issues in forwarding infrastructures (FIs). We present a general model for an FI, analyze potential security vulnerabilities, and present techniques to address these vulnerabilities. The main technique that we introduce in this paper is the use of simple lightweight cryptographic constraints on forwarding entries. We show that it is possible to prevent a large class of attacks on end-hosts and bound the flooding attacks that can be launched on the infrastructure nodes to a small constant value. Our mechanisms are general and apply to a variety of earlier proposals such as , DataRouter, and Network Pointers.     

Exploiting arrays with multiple invariances using MUSIC and MODE

This paper describes several new techniques for direction of arrival (DOA) estimation using arrays composed of multiple translated and uncalibrated subarrays. The new algorithms can be thought of as generalizations of the MUSIC, Root-MUSIC, and MODE techniques originally developed for fully calibrated arrays. The advantage of these new approaches is that the DOAs can be estimated using either a simple one-dimensional (1-D) search or by rooting a polynomial, as opposed to the multidimensional search required by multiple invariance (MI)-ESPRIT. When it can be applied, the proposed MI-MODE algorithm shares the statistical optimality of MI-ESPRIT. While MI-MUSIC and Root-MI-MUSIC are only optimal for uncorrelated sources, they perform better than a single invariance implementation of ESPRIT and are thus better suited for finding the initial conditions required by the MI-ESPRIT search     

On instrumental variable estimation of sinusoid frequencies and the parsimony principle

Multiple sinusoids in noise can be modeled as an ARMA process with the AR parameters satisfying certain symmetry relations. According to the "parsimony principle" the constraints on the AR parameters should he taken into account to get improved estimation accuracy. It is shown in this note that when estimating the AR parameters by a general instrumental-variable method, such a parsimony does not necessarily apply. However, the parsimony principle does hold when an optimal instrumental-variable method is used.     

Fast Implementation of Two-Dimensional APES and CAPON Spectral Estimators

The matched-filterbank spectral estimators APES and CAPON have recently received considerable attention in a number of applications. Unfortunately, their computational complexity tends to limit their usage in several cases – a problem that has previously been addressed by different authors. In this paper, we introduce a novel approach to the computation of the APES and CAPON spectra, which leads to a computational method that is considerably faster than all existing techniques. The new implementations of APES and CAPON are called fast APES and fast CAPON, respectively, and are developed for the two-dimensional case, with the one-dimensional case as a special case. Numerical examples are provided to demonstrate the application of APES to synthetic aperture radar (SAR) imaging, and to illustrate the reduction in computational complexity provided by our method.     

Optimal high-order Yule-Walker estimation of sinusoidal frequencies

The asymptotic properties of sinusoidal frequency estimators based on the high-order Yule-Walker (HOYW) equations were analyzed recently. The results of that analysis are used to propose two classes of frequency estimators; one class uses singular value decomposition, and the other uses a sparse matrix solution. Both classes entail two estimation steps: the first step generates initial estimates which are used to obtain an optimal weighting matrix, and the second step generates an optimally weighted estimate. Each two-step method produces asymptotically minimum variance estimates over all estimators of their class. The implementation of the proposed estimators is described in detail, and numerical examples are presented to evaluate their performance     

Performance analysis of forward-backward matched-filterbankspectral estimators

The problem of complex spectral estimation is of great interest in many applications. This paper studies the general class of the forward-backward matched-filterbank (MAFI) spectral estimators including the widely used Capon as well as the more recently introduced amplitude and phase estimation of a sinusoid (APES) methods. In particular, we show by means of a higher order expansion technique that the one-dimensional (1-D) Capon estimator underestimates the true spectrum, whereas the 1-D APES method is unbiased; we also show that the bias of the forward-backward Capon is half that of the forward-only Capon (to within a second-order approximation). Furthermore. We show that these results can be extended to the two-dimensional (2-D) Capon and APES estimators. Numerical examples are also presented to demonstrate quantitatively the properties of and the relation between these MAFI estimators